A Dendritic Neuron Model for Breast Cancer Classification

Breast cancer is the most common malignant tumor among women, and the incidence is on the rise all over the world, endangering women's life and health seriously, the prevention and treatment of this disease becomes important. Aiming at the classification problem of breast cancer, this paper uses the dendritic neuron model to mine and analyze the data, and determines the effective learning algorithm of the model for breast cancer data through comparative experiments. The experimental data were collected from two common breast cancer classification datasets in UCI database, and six classical learning algorithms were compared. The experimental results show that the dendritic neuron model has high accuracy, fast convergence, and remarkable classification performance for breast cancer.